Cardio and Data Science
Mapping Cardio Excersises with R
In 2022, I was introduced to spatial data analysis through the use of the programming language R.
I have long had interest in geography and mapping, and I was eager to develop a GIS toolbox which
would allow me to create insightful and visually appealing maps of my own. In an effort to grow my
skills (and to get in better shape) I committed to running and cycling on a regular basis, and recorded
gps data for every excersise I logged. Through the use of R, I have developed maps to visualise the routes
I frequent in 2 particular ways:
Heat maps showcase which routes are taken most often. They make use of kernel density estimation to generate a
'heat' raster image. This image showcases which routes are taken most frequently relative to each other.
Line maps showcase the cumulative reach of all gps points recorded. They are essentially a journal which records
the full extent of every route I've taken.
The buttons below may be used to navigate through the differing map types for jogging and cycling.